Landslides are one of the common geohazards in the mountainous terrain causing damage to properties and lives alike. The North-Eastern part of India is particularly vulnerable to landslides due to the hilly terrain and heavy rainfall. An extreme rainfall event which occurred from 9 to 15th of May 2022 in parts of Dima Hasao district of Assam resulted in a series of catastrophic landslides in the area. Out of the many, maximum damages were reported from the Haflong area. A massive mudflow was observed on 16th of May when a slope section to the North-West of the New Haflong railway station gave way which almost buried a passenger train. The frequent occurrence of the landslides in these areas highlight the need for robust means of understanding the causes of landslides, assess their potential impact, and develop strategies to minimize the damage they can cause. Numerical modelling is an effective technique for determining the potential damage caused by these catastrophes and for planning the mitigation strategies. Effective modelling of these events can be done with a proper understanding of the effects of different input parameters. In this regard, the landslide polygons for the area surrounding the New Haflong railway station were mapped using high-resolution bi-temporal (pre and post disaster) satellite images obtained from Google Earth Pro. A parametric analysis was then performed using the RAMMS software, which uses the depth-averaged method to understand the effect of the dry Coulomb type friction coefficient and viscous turbulent friction coefficient on the landslide polygons.